MétaCan
Menu
Back to cohort
Record W3185366810 · doi:10.1039/d1na00275a

Determination of the valence band edge of Fe oxide nanoparticles dispersed in aqueous solution through resonant photoelectron spectroscopy from a liquid microjet

2021· article· en· W3185366810 on OpenAlexaff
Giorgia Olivieri, Gregor Kladnik, D. Cvetko, Matthew A. Brown

Bibliographic record

VenueNanoscale Advances · 2021
Typearticle
Languageen
FieldEnergy
TopicIron oxide chemistry and applications
Canadian institutionsNational Research Council Canada
FundersJavna Agencija za Raziskovalno Dejavnost RSEidgenössische Technische Hochschule Zürich
KeywordsX-ray photoelectron spectroscopyAqueous solutionValence bandNanoparticleValence (chemistry)SpectroscopyOxideMaterials scienceEnhanced Data Rates for GSM EvolutionAnalytical Chemistry (journal)Chemical engineeringChemistryNanotechnologyPhysical chemistryNuclear magnetic resonancePhysicsBand gapChromatographyOptoelectronicsOrganic chemistryMetallurgyTelecommunicationsQuantum mechanics

Abstract

fetched live from OpenAlex

absorption edge is measured for 2 wt% aqueous solutions of FeOOH nanoparticles (NPs) and the valence band maximum (VBM) of the hydrated FeOOH nanoparticles is determined. We compare the obtained VBM value in aqueous solution to that of FeOOH NPs in the dry phase. We show that the valence band edge position of NPs in the liquid phase can be accurately predicted from the values obtained in the dry phase provided that a simple potential shift due to solution chemistry is applied. Our results demonstrate the suitability of resonant photoemission in measuring the electronic structure of strongly diluted nanosystems where the conventional non-resonant photoemission technique fails.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.408

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.253
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueNanoscale AdvancesSame topicIron oxide chemistry and applicationsFrench-language works237,207